research
∙
05/24/2023
The Behavior and Convergence of Local Bayesian Optimization
A recent development in Bayesian optimization is the use of local optimi...
share
research
∙
04/19/2023
Human-Computer Collaboration for Visual Analytics: an Agent-based Framework
The visual analytics community has long aimed to understand users better...
research
∙
11/28/2022
A Visual Active Search Framework for Geospatial Exploration
Many problems can be viewed as forms of geospatial search aided by aeria...
research
∙
10/21/2022
Local Bayesian optimization via maximizing probability of descent
Local optimization presents a promising approach to expensive, high-dime...
research
∙
08/09/2022
A Unified Comparison of User Modeling Techniques for Predicting Data Interaction and Detecting Exploration Bias
The visual analytics community has proposed several user modeling algori...
research
∙
02/08/2022
Nonmyopic Multiclass Active Search for Diverse Discovery
Active search is a setting in adaptive experimental design where we aim ...
research
∙
06/11/2021
Nonmyopic Multifidelity Active Search
Active search is a learning paradigm where we seek to identify as many m...
research
∙
10/16/2020
Active Visual Analytics: Assisted Data Discovery in Interactive Visualizations via Active Search
We propose the Active Visual Analytics technique (ActiveVA), an augmenta...
research
∙
09/13/2020
Competing Models: Inferring Exploration Patterns and Information Relevance via Bayesian Model Selection
Analyzing interaction data provides an opportunity to learn about users,...
research
∙
06/29/2020
Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees
Bayesian optimization is a sequential decision making framework for opti...
research
∙
06/17/2020
GPIRT: A Gaussian Process Model for Item Response Theory
The goal of item response theoretic (IRT) models is to provide estimates...
research
∙
09/10/2019
Efficient nonmyopic Bayesian optimization and quadrature
Finite-horizon sequential decision problems arise naturally in many mach...
research
∙
04/24/2019
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs
Graph structured data are abundant in the real world. Among different gr...
research
∙
02/26/2019
Automated Model Selection with Bayesian Quadrature
We present a novel technique for tailoring Bayesian quadrature (BQ) to m...
research
∙
11/21/2018
Efficient nonmyopic active search with applications in drug and materials discovery
Active search is a learning paradigm for actively identifying as many me...
research
∙
09/25/2018
Learning and Anticipating Future Actions During Exploratory Data Analysis
The goal of visual analytics is to create a symbiosis between human and ...
research
∙
02/13/2018
An Improved Bayesian Framework for Quadrature of Constrained Integrands
Quadrature is the problem of estimating intractable integrals, a problem...
research
∙
12/02/2016
Active Search for Sparse Signals with Region Sensing
Autonomous systems can be used to search for sparse signals in a large s...
research
∙
09/22/2016
Exact Sampling from Determinantal Point Processes
Determinantal point processes (DPPs) are an important concept in random ...
research
∙
07/02/2015
Anomaly Detection and Removal Using Non-Stationary Gaussian Processes
This paper proposes a novel Gaussian process approach to fault removal i...
research
∙
01/16/2015
Differentially Private Bayesian Optimization
Bayesian optimization is a powerful tool for fine-tuning the hyper-param...
research
∙
11/03/2014
Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature
We propose a novel sampling framework for inference in probabilistic mod...
research
∙
10/13/2014
Propagation Kernels
We introduce propagation kernels, a general graph-kernel framework for e...
research
∙
09/17/2012
Submodularity in Batch Active Learning and Survey Problems on Gaussian Random Fields
Many real-world datasets can be represented in the form of a graph whose...
research
∙
06/27/2012
